SolarAnywhere® Support Center

How can we help?

Home » Data Fields » Albedo In-depth

Albedo In-depth

General

Albedo is a measure of the fraction of the global horizontal irradiance that is reflected off the ground. Albedo is unitless and is expressed as a decimal, e.g., 0.20. The parameter is critical for estimating the gain from bifacial PV systems.

The best methods for albedo determination and bifacial modeling continue to evolve. For example, Sandia National Laboratories facilitates the Bifacial PV Project within the PV Performance Modeling Collaborative. An excellent summary of research relevant to bifacial modeling can be found on the project’s website.

Methodology

SolarAnywhere offers albedo data (in V3.5 and newer) to support bifacial system modeling. The data are based on satellite observations and modeling of surface albedo and snow cover. The spatial resolutions of these data are 1 km and 4 km nominal, respectively. SolarAnywhere customers can access albedo data with SolarAnywhere v3.5 and newer weather data versions. The data is available in all geographic regions and is updated monthly with SolarAnywhere historical data (approximately 1-2 months lag from real time).

SolarAnywhere albedo data is created in two main steps.

  1. For each location, the long-term monthly average snow-free albedo (MODIS MCD43GF white sky, 0.3-5 µm) is calculated. This represents the albedo of the ground, without snow, assuming diffuse illumination.
  2. Daily snow cover data is used to determine when the ground is covered in snow. If snow is present, the albedo is set to the average albedo of snow (0.6). The average albedo of snow was determined empirically by leveraging the reference dataset published by the DuraMAT consortium. The average includes a variety of locations and snow conditions.

Long-term averages (2013-2017) are used for the snow-free albedo because generally the ground does not change much from day to day and year to year (i.e., the daily and annual variability has little impact on energy simulations). Snow cover, however, must be a true time-series input because snow cover may be ephemeral, varies from year to year, and has a very significant impact on albedo and bifacial gain.

Using SolarAnywhere Albedo Data

For convenience, SolarAnywhere albedo data is available with all data types: Typical GHI/DNI year (TGY/TDY), average year, time series and probability of exceedance (PXX). Using time-series or average-year data types to determine the long-term average albedo is recommended.

SolarAnywhere uses industry-leading methods for generating albedo data. However, users should note the limitations of albedo data derived from remote sources, and how the data compares with ground-based measurements:

  • Albedo may vary significantly within a small area. SolarAnywhere albedo data have a maximum resolution of approximately 1 km. The data may not be representative of the specific location under the solar array. This is especially relevant to small projects and commercial rooftops that may have a distinct surface. Similarly, ground-based albedometers measure a relatively small area compared to remote sources.
  • The albedo data are historical averages. Changes in land use and site preparation may change the surface albedo. The post-construction surface condition of the site should be considered for bifacial system modeling.
  • In general, careful ground-based albedo measurements, if available, are preferred for solar project financing. However, because snow cover varies from year to year, the impact of snow should be derived from a long-term source such as SolarAnywhere.
  • The following study evaluates the remote-sensed albedo data available in NREL’s NSRDB against ground measurements for estimating bifacial system performance:
    Marion, Bill. Measured and Satellite-Derived Albedo Data for Estimating Bifacial Photovoltaic System Performance. United States: N. p., 2020. Web. doi:10.1016/j.solener.2020.12.050
  • While SolarAnywhere albedo data has several improvements over the NSRDB data, including higher spatial resolution and a more realistic value for the average albedo of snow, the methodology is similar.
  • There is a known issue (“Incorrect representation of aerosol quantities”) impacting MODIS data, particularly over arid bright surfaces such as the Sahara and Arabian Peninsula areas. The issue affects all C6 MCD43 products. The issue will be corrected in future versions.